CN111792256B - Feeding system that intellectual detection system and intelligence are hierarchical stores - Google Patents
Feeding system that intellectual detection system and intelligence are hierarchical stores Download PDFInfo
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- CN111792256B CN111792256B CN202010695309.2A CN202010695309A CN111792256B CN 111792256 B CN111792256 B CN 111792256B CN 202010695309 A CN202010695309 A CN 202010695309A CN 111792256 B CN111792256 B CN 111792256B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
- B65G1/02—Storage devices
- B65G1/04—Storage devices mechanical
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
- B65G1/02—Storage devices
- B65G1/04—Storage devices mechanical
- B65G1/137—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
- B65G1/1373—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed for fulfilling orders in warehouses
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G35/00—Mechanical conveyors not otherwise provided for
Abstract
Compared with a common feeding system, the intelligent detection and intelligent grading storage feeding system comprises a sampling module for quantitatively sampling the materials in a storage tank, a detection module for detecting the physical and chemical characteristics of samples obtained by the sampling module, a material grading system for further grading and selecting the materials based on big data cloud analysis on the detection value of the detection module, and an automatic distribution and conveying module for intelligently distributing a target warehouse of a transfer machine according to the grading result of the materials and automatically conveying the target warehouse at a fixed point by the transfer machine. The feeding system has high intellectualization, effectively enhances the intelligent monitoring of materials, improves the efficiency of a transportation system and effectively reduces the labor cost.
Description
Technical Field
The invention relates to the field of feeding systems, in particular to a feeding system with intelligent detection and intelligent hierarchical storage.
Background
The material transportation refers to the activities which are carried out in the same site category and mainly aim at changing the material storage state and the space position. The material handling is very important to the improvement of warehouse operating efficiency, and the material handling also directly influences the production efficiency. In a production type enterprise, a worker usually takes charge of the links of conveying and warehousing packaged materials, storing the packaged materials in a warehouse, transporting the packaged materials to a storage warehouse by a transporting device, and the like. The specific material handling operation mainly comprises horizontal or inclined plane movement-handling operation, vertical movement-loading and unloading operation, stacking or goods taking-lifting or descending operation, turning-rotating operation around a vertical line and turning-rotating operation around a horizontal axis. The basic content of material handling is material, movement and method. The accessory assembly worker needs to manually scan the bar codes one by one for each accessory, and adapts the types, the accuracy of material transportation to a storage warehouse is guaranteed through checking, and a follow-up quality inspector needs to repeat the process for checking. Obviously, the operation efficiency of the process is very low, the accessory bar codes can only be passively found and verified without any other prompt, the placing positions of the materials are not restricted, and the materials are scattered and easy to make mistakes.
Typical prior art feed systems are: including smashing the jar, throwing the feed bin, throwing material jar and blending tank, throw the material jar and set up at the tank deck of blending tank, throw the feed bin and throw and be provided with the vacuum between the material jar and take out the pressure equipment and put and transmit, smash the jar and throw the material storehouse and adopt the transmission track to be connected. Conventional feeding systems do not have the capability of detecting the physicochemical properties of the materials and further determining the quality grade of each batch of materials, and when the materials are used, the production results of the production line are not good due to the uneven quality of the materials.
The invention aims to solve the problems that errors are caused by manual operation in the material transportation process and are difficult to find, intelligent separated storage cannot be carried out according to the quality grade of materials, wrong transportation of a transportation machine cannot be checked, the labor cost of a feeding system is high, the transportation efficiency is low and the like in the field, and the research team provides the invention.
Disclosure of Invention
The invention aims to provide a feeding system which is more intelligent, high-efficiency and strong in practicability and is used for intelligent detection and intelligent hierarchical storage, aiming at the defects of the existing feeding system.
In order to overcome the defects of the prior art, the invention adopts the following technical scheme:
the utility model provides a feeding system that intellectual detection system and intelligence are hierarchical stores, including the storage jar that stores the material, to store the jar the packing apparatus that the material was packed and is handled and will through belt conveyer the material is loaded and is carried the material to the transfer machine in target warehouse, feeding system still includes right store in jar the material carry out the sampling module of quantitative sampling, detect the detection module of the physicochemical characteristic of the sample that sampling module acquireed, right detection module's detection numerical value is further right based on big data cloud analysis the material grading system that the material carries out the grade selection and according to the hierarchical result intelligent allocation of material shift the target warehouse of machine and by transfer the automatic fixed point transportation's of machine automatic allocation transport module.
Optionally, the sampling module performs signal feedback between a weight sensor for detecting the weight of the sample and a controller for controlling a controllable valve of the storage tank, so as to control the opening of the controllable valve and further control the sampling speed and the quality of the sample.
Optionally, the detection module comprises a moisture detection unit for detecting moisture of the sample, a particle size detection unit for detecting the particle size of the material, a component detection unit for detecting the content of the components of the sample, and a data acquisition module for collecting detection information of the detection module and sending the detection information to the material classification system.
Optionally, the material grading system includes a data receiving module for receiving the characteristic parameter data of the sample sent by the data collecting module; a database for storing corresponding evaluation grading schemes and standard feature states for different kinds of the materials; the model building module is used for building a characteristic state model based on the characteristic parameter data of the material detected by the detection module; the calculation processing module is used for extracting matching parameters matched with the standard characteristic state model from the characteristic state model, and calculating and analyzing the matching parameter data of the characteristics of the standard characteristic state model to obtain a grading result corresponding to the quality inspection evaluation of the material; and according to the grade result of the material, calling data information related to the material from the database and generating a suggestion generation module of a corresponding processing scheme.
Optionally, the automatic distribution conveying module receives a classification result of the material classification system on the material through a control system to form a specific position information number of a target warehouse for storing the material, and the control system generates transportation distribution information according to the position signal and sends the transportation distribution information to a control end of the transfer machine to control the transfer machine to transport the material on the belt conveyor to the specific motion of the target warehouse.
The beneficial effects obtained by the invention are as follows:
1. can carry out automatic ration sampling to the material and detect.
2. The quality grade of the material can be obtained based on big data cloud analysis.
3. Can improve the utilization ratio to the material of different grades according to the grade distribution of material to corresponding warehouse.
4. The production result is not satisfactory because of the uneven quality grade of the material can be effectively avoided.
5. The high-intelligence feeding system effectively reduces the labor cost of the feeding system.
6. The efficiency of feeding system has effectively been improved.
Drawings
The invention will be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate corresponding parts throughout the different views.
Fig. 1 is a schematic flow chart of the feeding system for intelligent detection and intelligent hierarchical storage according to the present invention.
FIG. 2 is a flow chart of a sampling module according to the present invention.
FIG. 3 is a schematic flow chart of the detection module according to the present invention.
FIG. 4 is a schematic flow diagram of the material classification system of the present invention.
Fig. 5 is a schematic structural view of the belt conveyor of the present invention.
Fig. 6 is a schematic view of the structure of the transfer machine of the present invention.
Fig. 7 is an experimental diagram of the feeding system for intelligent detection and intelligent hierarchical storage according to the present invention.
Detailed Description
In order to make the objects and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the following embodiments; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. Other systems, methods, and/or features of the present embodiments will become apparent to those skilled in the art upon review of the following detailed description. It is intended that all such additional systems, methods, features and advantages be included within this description, be within the scope of the invention, and be protected by the accompanying claims. Additional features of the disclosed embodiments are described in, and will be apparent from, the detailed description that follows.
The same or similar reference numerals in the drawings of the embodiments of the present invention correspond to the same or similar components; in the description of the present invention, it should be understood that if there is an orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", etc. based on the orientation or positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but it is not intended to indicate or imply that the device or component referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and are not to be construed as limiting the present patent, and the specific meaning of the terms described above will be understood by those of ordinary skill in the art according to the specific circumstances.
The first embodiment is as follows:
in the embodiment, a feeding system of a sampling module capable of intelligently and quantitatively sampling materials for multiple times is constructed; it includes the storage jar that stores the material, right store the jar packing apparatus that the material was packed and is handled and will through belt conveyer the material is loaded and is carried to the transfer machine in target warehouse, feeding system still include right store in the jar the material carry out the sampling module of ration sample, detect the detection module of the physicochemical characteristic of the sample that sampling module acquireed, right detection module's detection numerical value is further right based on big data cloud analysis the material grading system that the material carries out the grade and assesses and according to the hierarchical result intelligent distribution of material the target warehouse of transfer machine and by transfer machine carries out the automatic allocation transport module that the automatic fixed point was transported, sampling module carries out signal feedback through the weight sensor that detects sample weight and control between the controller of the controllable valve of storage jar thereby control the opening of controllable valve and then the speed of control sample And the quality of the sample, the detection module comprises a moisture detection unit for detecting the moisture of the sample, a particle size detection unit for detecting the granularity of the material, a component detection unit for detecting the content of the components of the sample, and a data acquisition module for collecting detection information of the detection module and sending the detection information to a material grading system, the material grading system comprises a data receiving module for receiving characteristic parameter data of the sample sent by the data acquisition module, a database for storing corresponding evaluation grading schemes and standard characteristic states of different types of materials, a model establishing module for establishing a characteristic state model based on the characteristic parameter data of the materials detected by the detection module, a matching parameter matched with the standard characteristic state model is extracted from the characteristic state model, and the matching parameter data of the characteristics of the standard characteristic state model is calculated and analyzed to obtain the matching parameter data corresponding to the materials The automatic distribution and conveying module receives the grading result of the material grading system through a control system to form a specific position information number of a target warehouse for storing the material, and the control system generates transportation distribution information according to the position signal and sends the transportation distribution information to a control end of the transfer machine so as to control the transfer machine to transport the material on the belt conveyor to the specific movement of the target warehouse;
the sampling module is configured to extract at least two parallel samples with the same quality from a material, so as to ensure the referential property of a detection result, the sampling module comprises a sampling device and an information feedback unit for controlling the sampling device to perform sampling work, wherein the sampling device comprises a sample storage bottle for placing the samples and a mechanical arm which is connected with the sample storage bottle and controls the sample storage bottle to move to the detection module, the motion track of the sampling device for transferring the samples to the detection module is programmed in advance in the controller, and the controller controls the mechanical arm to move along a specified track;
the information feedback unit comprises at least one weight sensor, a controller and an information transmitter, the sampling device determines the weight of the sample in the sample storage bottle by using the at least one weight sensor, wherein at least one stirring device is arranged in the storage tank, so that the material is uniformly distributed, the sample taken by the sampling device is representative, the deviation of the detection result of the detection module caused by human factors is avoided, the reference degree of the detection result is ensured, and the production has many practical meanings, the controller is configured to monitor a material sampling line entering the sampling device, when the material transportation work is started, the controller can send an opening instruction to the sampling device, the sampling device reaches the controllable valve of the storage tank according to the instruction, the information transmitter of the sampling device can send a signal for opening the valve to the controller, the controller controls the controllable valve opening to enable the sampling device to sample, the weight sensor is arranged in the sampling device, when the weight of the sample reaches a certain range close to the preset sampling weight, the weight sensor can generate a deceleration signal and send the deceleration signal to the controller through the information transmitter so as to control the opening of the controllable valve to be smaller, so that the situation that the opening is too large and the quantity of the material entering the sampling device is not well controlled is prevented, after the slow feeding, when the value of the weight sensor reaches a preset threshold value, the weight sensor sends a valve port closing signal to the controller, so that the controller controls the valve port to be closed, then completing quantitative sampling, and transporting the sample to the detection device by the sampling device according to a motion track preset in the controller, so that the detection module further detects the sample;
the intelligent quantitative sampling times of the sampling module can be selected by a person skilled in the art according to actual requirements, and the sampling module provided by the invention can be used for conveniently and reliably detecting the material.
Example two:
in the embodiment, a feeding system of a detection module is constructed, which can detect the physicochemical characteristics of a sample which is intelligently sampled for a plurality of times by a sampling device; it includes the storage jar that stores the material, right store the jar packing apparatus that the material was packed and is handled and will through belt conveyer the material is loaded and is carried to the transfer machine in target warehouse, feeding system still include right store in the jar the material carry out the sampling module of ration sample, detect the detection module of the physicochemical characteristic of the sample that sampling module acquireed, right detection module's detection numerical value is further right based on big data cloud analysis the material grading system that the material carries out the grade and assesses and according to the hierarchical result intelligent distribution of material the target warehouse of transfer machine and by transfer machine carries out the automatic allocation transport module that the automatic fixed point was transported, sampling module carries out signal feedback through the weight sensor that detects sample weight and control between the controller of the controllable valve of storage jar thereby control the opening of controllable valve and then the speed of control sample And the quality of the sample, the detection module comprises a moisture detection unit for detecting the moisture of the sample, a particle size detection unit for detecting the granularity of the material, a component detection unit for detecting the content of the components of the sample, and a data acquisition module for collecting detection information of the detection module and sending the detection information to a material grading system, the material grading system comprises a data receiving module for receiving characteristic parameter data of the sample sent by the data acquisition module, a database for storing corresponding evaluation grading schemes and standard characteristic states of different types of materials, a model establishing module for establishing a characteristic state model based on the characteristic parameter data of the materials detected by the detection module, a matching parameter matched with the standard characteristic state model is extracted from the characteristic state model, and the matching parameter data of the characteristics of the standard characteristic state model is calculated and analyzed to obtain the matching parameter data corresponding to the materials The automatic distribution and conveying module receives the grading result of the material grading system through a control system to form a specific position information number of a target warehouse for storing the material, and the control system generates transportation distribution information according to the position signal and sends the transportation distribution information to a control end of the transfer machine so as to control the transfer machine to transport the material on the belt conveyor to the specific movement of the target warehouse;
the sampling module is configured to extract at least two parallel samples with the same quality from a material, so as to ensure the referential property of a detection result, the sampling module comprises a sampling device and an information feedback unit for controlling the sampling device to perform sampling work, wherein the sampling device comprises a sample storage bottle for placing the samples and a mechanical arm which is connected with the sample storage bottle and controls the sample storage bottle to move to the detection module, the motion track of the sampling device for transferring the samples to the detection module is programmed in advance in the controller, and the controller controls the mechanical arm to move along a specified track;
the information feedback unit comprises at least one weight sensor, a controller and an information transmitter, the sampling device determines the weight of the sample in the sample storage bottle by using the at least one weight sensor, wherein at least one stirring device is arranged in the storage tank, so that the material is uniformly distributed, the sample taken by the sampling device is representative, the deviation of the detection result of the detection module caused by human factors is avoided, the reference degree of the detection result is ensured, and the production has many practical meanings, the controller is configured to monitor a material sampling line entering the sampling device, when the material transportation work is started, the controller can send an opening instruction to the sampling device, the sampling device reaches the controllable valve of the storage tank according to the instruction, the information transmitter of the sampling device can send a signal for opening the valve to the controller, the controller controls the controllable valve opening to enable the sampling device to sample, the weight sensor is arranged in the sampling device, when the weight of the sample reaches a certain range close to the preset sampling weight, the weight sensor can generate a deceleration signal and send the deceleration signal to the controller through the information transmitter so as to control the opening of the controllable valve to be smaller, so that the situation that the opening is too large and the quantity of the material entering the sampling device is not well controlled is prevented, after the slow feeding, when the value of the weight sensor reaches a preset threshold value, the weight sensor sends a valve port closing signal to the controller, so that the controller controls the valve port to be closed, then completing quantitative sampling, and transporting the sample to the detection device by the sampling device according to a motion track preset in the controller, so that the detection module further detects the sample;
the intelligent quantitative sampling times of the sampling module can be selected by a person skilled in the art according to actual requirements, and the sampling module provided by the invention can be used for conveniently and reliably detecting the material;
in a production line for producing materials and a quality inspection production line taking the materials as production raw materials, screening of the materials is particularly important for the production line, the manual quality inspection production line is easy to generate human errors due to fatigue caused by mechanical work of workers, and the quality inspection of fuel materials is complicated and time-consuming, labor-consuming, so that the production line is high in cost and low in efficiency;
the detection module comprises a moisture detection unit, a particle size detection unit, a component detection unit and a data acquisition module for collecting, storing and sending data detected by the detection module to the material grading system, wherein the moisture detection unit comprises at least one moisture detector for detecting the moisture content of the sample, the moisture detector can be selected by a person skilled in the art according to actual needs based on any type of moisture detector based on resistance, inductance, reactance, capacitance, image and/or spectrum, the component detection device can be selected by a person skilled in the art by detecting the content of the components such as ash, volatile components, C, H, N, S, O, Cl, Si, Ca, K, Na and/or P of the material, and the detection content of the component detection device can be selected and combined by a person skilled in the art according to actual needs, the particle size detection unit comprises a camera device for shooting a sample picture and a processing module for reading the gray value distribution of the picture by using software and calculating the particle size of the material, the processing module records the peak distance of the highest gray distribution by scanning a gray matrix of the region where the particles are located line by line, wherein the line sequence corresponding to the maximum distance is the center of the particles in the x direction, the corresponding column sequence is the center of the y direction, the gray distribution of the image is scanned line by line around the center position of the particles, the gray distribution curve is intersected with the average gray value of the image, at least two intersection points are inevitably present in the particle gray distribution range, two intersection points near the gray peak value of the imaging edge are selected, the distance between the two intersection points is recorded, and the maximum value is found out for all the distances in the line-by-line scanning range, the value is the image diameter Dix of the particles detected in the x-axis direction, the image diameter Diy of the particles detected in the y-axis direction is measured by adopting the same judgment standard, the diameter Dix-Diy exists for the round particles, and the average value of Dix and Diy is calculated, so that the image diameter Di of the detected particles is the particle size of the material;
in the process of detecting the material by the detection module, the data acquisition module records the moisture reading, the particle size reading and the component value reading of the material detected by the detection module in real time, and simultaneously stores the detection result acquired each time through the storage device so as to provide real-time data and historical data, and sends the batch number or processing number distribution of the material and the sample and the recorded data signal to the material grading system for the next-step material grading processing.
Example three:
in the embodiment, a feeding system with a material grading system based on big data cloud analysis is constructed; the utility model provides a feeding system that intellectual detection system and intelligence are hierarchical stores, including the storage jar that stores the material, to store jar the packing apparatus that the material was packed and is handled and will through belt conveyer the material is loaded and is carried the transfer machine of material to target warehouse, feeding system still includes right store in jar the material carry out the sampling module of ration sample, detect the detection module of the physical and chemical characteristics of the sample that sampling module acquireed, right detection module's detection numerical value is further right based on big data cloud analysis the material grading system that the material carries out grade selection and according to the hierarchical result intelligent allocation of material shift the target warehouse of machine and by transfer machine carries out the automatic distribution transport module that automatic fixed point transported, thereby sampling module carries out signal feedback control through the weighing transducer that detects sample weight and control between the controller of the controllable valve of jar stores thereby control The opening of the controllable valve further controls the sampling speed and the quality of the sample, the detection module comprises a moisture detection unit for detecting moisture of the sample, a particle size detection unit for detecting the granularity of the material, a component detection unit for detecting the content of components of the sample, and a data acquisition module for collecting detection information of the detection module and sending the detection information to the material grading system, the material grading system comprises a data receiving module for receiving characteristic parameter data of the sample sent by the data acquisition module, a database for storing corresponding evaluation grading schemes and standard characteristic states of different types of the material, a model establishing module for establishing a characteristic state model based on the characteristic parameter data of the material detected by the detection module, and a matching parameter matched with the standard characteristic state model is extracted from the characteristic state model and enters the matching parameter data of the characteristic of the standard characteristic state model The automatic distribution and conveying system comprises a calculation processing module for performing calculation and analysis processing to obtain a grading result corresponding to quality inspection evaluation of a material, and a suggestion generation module for calling data information related to the material in the database according to the grading result of the material and generating a corresponding processing scheme, wherein the automatic distribution and conveying module receives the grading result of the material by the material grading system through a control system to form a specific position information number of a target warehouse for storing the material, and the control system generates transportation distribution information according to the position signal and sends the transportation distribution information to a control end of the transfer machine to control the transfer machine to transport the material on the belt conveyor to the specific movement of the target warehouse;
the sampling module is configured to extract at least two parallel samples with the same quality from a material, so as to ensure the referential property of a detection result, the sampling module comprises a sampling device and an information feedback unit for controlling the sampling device to perform sampling work, wherein the sampling device comprises a sample storage bottle for placing the samples and a mechanical arm which is connected with the sample storage bottle and controls the sample storage bottle to move to the detection module, the motion track of the sampling device for transferring the samples to the detection module is programmed in advance in the controller, and the controller controls the mechanical arm to move along a specified track;
the information feedback unit comprises at least one weight sensor, a controller and an information transmitter, the sampling device determines the weight of the sample in the sample storage bottle by using the at least one weight sensor, wherein at least one stirring device is arranged in the storage tank, so that the material is uniformly distributed, the sample taken by the sampling device is representative, the deviation of the detection result of the detection module caused by human factors is avoided, the reference degree of the detection result is ensured, and the production has many practical meanings, the controller is configured to monitor a material sampling line entering the sampling device, when the material transportation work is started, the controller can send an opening instruction to the sampling device, the sampling device reaches the controllable valve of the storage tank according to the instruction, the information transmitter of the sampling device can send a signal for opening the valve to the controller, the controller controls the controllable valve opening to enable the sampling device to sample, the weight sensor is arranged in the sampling device, when the weight of the sample reaches a certain range close to the preset sampling weight, the weight sensor can generate a deceleration signal and send the deceleration signal to the controller through the information transmitter so as to control the opening of the controllable valve to be smaller, so that the situation that the opening is too large and the quantity of the material entering the sampling device is not well controlled is prevented, after the slow feeding, when the value of the weight sensor reaches a preset threshold value, the weight sensor sends a valve port closing signal to the controller, so that the controller controls the valve port to be closed, then completing quantitative sampling, and transporting the sample to the detection device by the sampling device according to a motion track preset in the controller, so that the detection module further detects the sample;
the intelligent quantitative sampling times of the sampling module can be selected by a person skilled in the art according to actual requirements, and the sampling module provided by the invention can be used for conveniently and reliably detecting the material;
in a production line for producing materials and a quality inspection production line taking the materials as production raw materials, screening of the materials is particularly important for the production line, the manual quality inspection production line is easy to generate human errors due to fatigue caused by mechanical work of workers, and the quality inspection of fuel materials is complicated and time-consuming, labor-consuming, so that the production line is high in cost and low in efficiency;
the detection module comprises a moisture detection unit, a particle size detection unit, a component detection unit and a data acquisition module for collecting, storing and sending data detected by the detection module to the material grading system, wherein the moisture detection unit comprises at least one moisture detector for detecting the moisture content of the sample, the moisture detector can be selected by a person skilled in the art according to actual needs based on any type of moisture detector based on resistance, inductance, reactance, capacitance, image and/or spectrum, the component detection device can be selected by a person skilled in the art by detecting the content of the components such as ash, volatile components, C, H, N, S, O, Cl, Si, Ca, K, Na and/or P of the material, and the detection content of the component detection device can be selected and combined by a person skilled in the art according to actual needs, the particle size detection unit comprises a camera device for shooting a sample picture and a processing module for reading the gray value distribution of the picture by using software and calculating the particle size of the material, the processing module records the peak distance of the highest gray distribution by scanning a gray matrix of the region where the particles are located line by line, wherein the line sequence corresponding to the maximum distance is the center of the particles in the x direction, the corresponding column sequence is the center of the y direction, the gray distribution of the image is scanned line by line around the center position of the particles, the gray distribution curve is intersected with the average gray value of the image, at least two intersection points are inevitably present in the particle gray distribution range, two intersection points near the gray peak value of the imaging edge are selected, the distance between the two intersection points is recorded, and the maximum value is found out for all the distances in the line-by-line scanning range, the value is the image diameter Dix of the particles detected in the x-axis direction, the image diameter Diy of the particles detected in the y-axis direction is measured by adopting the same judgment standard, the diameter Dix-Diy exists for the round particles, and the average value of Dix and Diy is calculated, so that the image diameter Di of the detected particles is the particle size of the material;
in the process of detecting the materials by the detection module, the data acquisition module records various detection results of the detection module, such as moisture readings, particle size readings and component value readings of the materials detected by the detection module in real time, stores the detection result acquired each time through the storage device so as to provide real-time data and historical data, and sends batch number or processing number distribution of the materials and samples and the recorded data signals to the material grading system for next-step material grading processing;
the material grading system comprises a data control system for receiving characteristic parameter data of material detection sent by a data acquisition module; the database is used for storing corresponding evaluation grading schemes of different types of materials and standard characteristic states of the different materials; the model building module is used for building a corresponding characteristic state model based on characteristic parameter data of the material detected by the detection module and storing the characteristic state model, wherein the characteristic parameter data at least comprises at least one of parameter data of the type, the particle size, the moisture content data and the content data of each element component of the material; the calculation processing module is used for extracting matching parameters matched with the standard characteristic state model from the characteristic state model, and calculating and analyzing the matching parameter data of the characteristics of the standard characteristic state model to obtain a grading result corresponding to the quality inspection evaluation of the material; and a suggestion generation module for calling data information related to the failing materials from the database according to the evaluation results of the failing materials and judging the appropriate use of the failing materials according to the component proportions of the low-quality failing materials and the failing materials and generating corresponding processing schemes, wherein for example, when the analysis result report shows that the moisture of the materials is more than or equal to 19%, the analysis result report suggests that the materials are dried at the temperature of 120 ℃;
when the material grading based on big data cloud analysis is applied to a server, an evaluation result and a material suggestion indication scheme can be displayed through a human-computer interaction interface, or the evaluation result and the material suggestion indication scheme are sent to material terminal equipment, and when the material grading based on big data cloud analysis is applied to an intelligent terminal, the material grading based on big data cloud analysis can be selected by a person skilled in the art to be applied in the form of an APP and/or a website according to actual requirements;
in the big data cloud analysis-based material grading, the model building module builds a standard characteristic state model and a plurality of characteristic state models based on different characteristic parameter combinations of the materials detected by the detection module, the model establishing module establishes at least one standard characteristic state model by establishing different characteristic parameter combinations of the standard characteristic state models according to parameters such as the types, the moisture, the particle sizes, the contents of various element components and the like of the materials, the calculation processing module extracts matching parameters matched with a standard characteristic state model from the characteristic state model and has a proportional relation to the matching parameters of the standard characteristic state model, comparing the standard characteristic state models, and calculating the proportional relation according to the standards of different types of materials to obtain the grading result of the materials;
a user can open and use the material grading system through the intelligent terminal, check corresponding batches of materials at corresponding platform positions, and finally check grading results and suggested indication schemes of the materials through the system or send the grading results and the suggested indication schemes of the materials to terminal equipment of the materials through a server which is embedded into the material grading system in advance;
the material grading system can upload and update the types of materials, detection standards corresponding to the types of the materials and related information in real time, the material grading system applies a precise prediction big data cloud analysis engine, so that a quality inspection report obtained by calculation is more standardized, clear, understandable and concise, the output mode is flexible and changeable, meanwhile, the inspected characteristic information of the materials is compared with the standard material information of a database, a quality inspection table is generated and stored in an information storage system, the cloud analysis engine compares the information of the low-grade and failing materials with the information of the database to generate a material abnormity report and a corresponding suggestion indication scheme, a worker selects a proper method for further processing according to the material abnormity report and the suggestion indication scheme, high utilization is realized, waste is reduced, and the specific reason that each batch of the unqualified goods are not inspected is conveniently mastered, so as to improve the storage management and the post problem processing;
compared with the prior art that intelligent equipment cannot evaluate the characteristic state of the material to grade the quality of the material, the material grading system based on the big data cloud analysis adopts the standard characteristic state model constructed based on the existing material parameter data recorded in the database, predicts and grades the characteristic state of the material according to the model, and calculates the recommended indication scheme corresponding to the evaluation result, so that the evaluation result is good in accuracy and high in reference degree.
Although the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications may be made without departing from the scope of the invention. That is, the methods, systems, and devices discussed above are examples. Various configurations may omit, substitute, or add various procedures or components as appropriate. For example, in alternative configurations, the methods may be performed in an order different than that described, and/or various components may be added, omitted, and/or combined. Moreover, features described with respect to certain configurations may be combined in various other configurations, as different aspects and elements of the configurations may be combined in a similar manner. Further, elements therein may be updated as technology evolves, i.e., many elements are examples and do not limit the scope of the disclosure or claims.
Specific details are given in the description to provide a thorough understanding of the exemplary configurations including implementations. However, configurations may be practiced without these specific details, for example, well-known circuits, processes, algorithms, structures, and techniques have been shown without unnecessary detail in order to avoid obscuring the configurations. This description provides example configurations only, and does not limit the scope, applicability, or configuration of the claims. Rather, the foregoing description of the configurations will provide those skilled in the art with an enabling description for implementing the described techniques. Various changes may be made in the function and arrangement of elements without departing from the spirit or scope of the disclosure.
In conclusion, it is intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that these examples are illustrative only and are not intended to limit the scope of the invention. After reading the description of the invention, the skilled person can make various changes or modifications to the invention, and these equivalent changes and modifications also fall into the scope of the invention defined by the claims.
Claims (2)
1. A feeding system for intelligent detection and intelligent grading storage comprises a storage tank for storing materials, a packing device for packing the materials in the storage tank, and a transfer machine for loading the materials and carrying the materials to a target warehouse through a belt conveyor; the feeding system also comprises a sampling module for quantitatively sampling the materials in the storage tank, a detection module for detecting the physical and chemical properties of samples obtained by the sampling module, a material grading system for further grading and selecting the materials based on big data cloud analysis on the detection value of the detection module, and an automatic distribution and conveying module for intelligently distributing a target warehouse of the transfer machine according to the grading result of the materials and automatically conveying the target warehouse at a fixed point by the transfer machine; it is characterized in that the preparation method is characterized in that,
the sampling module performs signal feedback between a weight sensor for detecting the weight of a sample and a controller for controlling a controllable valve of the storage tank so as to control the opening of the controllable valve and further control the sampling speed and the quality of the sample;
the detection module comprises a moisture detection unit for detecting the moisture of the sample, a particle size detection unit for detecting the granularity of the material, a component detection unit for detecting the content of the components of the sample, and a data acquisition module for collecting the detection information of the detection module and sending the detection information to the material grading system;
wherein, the particle size detection unit comprises a camera shooting device for shooting a sample picture and a processing module for reading the gray value distribution of the picture by using software and calculating the particle diameter of the material, the processing module records the peak distance of the highest gray distribution by scanning the gray matrix of the area where the particles are located line by line, the line sequence corresponding to the maximum distance is the center of the particles in the x direction, the corresponding column sequence is the center of the y direction, the gray distribution of the image is scanned line by line around the center position of the particles, the curve of the gray distribution is intersected with the average gray value of the image, at least two intersection points are inevitably present in the particle gray distribution range, two intersection points near the gray peak value of the imaging edge are selected, the distance between the two intersection points is recorded, and the maximum value is found out for all the distances in the line-by-line scanning range, the value is the image diameter Dix of the particles detected along the x-axis direction, the image diameter Diy of the particles detected along the y-axis direction is measured by adopting the same judgment standard, the diameter of the round particles is Dix-Diy, the average value of Dix and Diy is calculated, and the average value is used as the image diameter Di of the detected particles, namely the particle size of the material;
the material grading system comprises a data control system for receiving characteristic parameter data of material detection sent by the data acquisition module; the database is used for storing corresponding evaluation grading schemes of different types of materials and standard characteristic states of the different materials; the model building module is used for building a corresponding characteristic state model based on characteristic parameter data of the material detected by the detection module and storing the characteristic state model, wherein the characteristic parameter data comprises at least one of parameter data of the type, the particle size, the moisture content data and the content data of each element component of the material; the calculation processing module is used for extracting matching parameters matched with the standard characteristic state model from the characteristic state model, and calculating and analyzing the matching parameter data of the characteristics of the standard characteristic state model to obtain a grading result corresponding to the quality inspection evaluation of the material; the suggestion generation module is used for calling data information related to the failing materials from the database according to the evaluation result of the failing materials, judging the appropriate use of the failing materials according to the low quality and the component proportion of the failing materials and generating a corresponding processing scheme;
when the material classification based on big data cloud analysis is applied to a server, an evaluation result and a material suggestion indication scheme can be displayed through a human-computer interaction interface, or the evaluation result and the material suggestion indication scheme are sent to a material terminal device.
2. The feeding system of claim 1, wherein the automatic distribution conveying module receives a classification result of the material classification system on the material through a control system to form a specific position signal of a target warehouse for storing the material, and the control system generates conveying distribution information according to the position signal and sends the conveying distribution information to a control end of the transfer machine so as to control the transfer machine to convey the material on the belt conveyor to the specific movement of the target warehouse.
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